Pion, Kaon, and Proton Production in Central Pb-Pb Collisions at root s(NN)=2.76 TeV

In this Letter we report the first results on pi(+/-), K-+/-, p, and (p) over bar production at midrapidity (vertical bar y vertical bar < 0.5) in central Pb-Pb collisions at root s(NN) = 2.76 TeV, measured by the ALICE experiment at the LHC. The p(T) distributions and yields are compared to previous results at root s(NN) = 200 GeV and expectations from hydrodynamic and thermal models. The spectral shapes indicate a strong increase of the radial flow velocity with root s(NN), which in hydrodynamic models is expected as a consequence of the increasing particle density. While the K/pi ratio is in line with predictions from the thermal model, the p/pi ratio is found to be lower by a factor of about 1.5. This deviation from thermal model expectations is still to be understood.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

Independent predictors and a prognostic model for surgical outcome in refractory frontal lobe epilepsy

Purpose: Refractory frontal lobe epilepsy (FLE) remains one of the most challenging surgically remediable epilepsy syndromes. Nevertheless, definition of independent predictors and predictive models of postsurgical seizure outcome remains poorly explored in FLE. Methods: We retrospectively analyzed data from 70 consecutive patients with refractory FLE submitted to surgical treatment at our center from July 1994 to December 2006. Univariate results were submitted to logistic regression models and Cox proportional hazards regression to identify isolated risk factors for poor surgical results and to construct predictive models for surgical outcome in FLE. Results: From 70 patients submitted to surgery, 45 patients (64%) had favorable outcome and 37 (47%) became seizure free. Isolated risk factors for poor surgical outcome are expressed in hazard ratio (H.R.) and were time of epilepsy (H.R.=4.2; 95% C.I.=.1.5-11.7; p=0.006), ictal EEG recruiting rhythm (H.R. = 2.9; 95% C.I. = 1.1-7.7; p=0.033); normal MRI (H.R. = 4.8; 95% C.I. = 1.4-16.6; p = 0.012), and MRI with lesion involving eloquent cortex (H.R. = 3.8; 95% C.I. = 1.2-12.0; p = 0.021). Based on these variables and using a logistic regression model we constructed a model that correctly predicted long-term surgical outcome in up to 80% of patients. Conclusion: Among independent risk factors for postsurgical seizure outcome, epilepsy duration is a potentially modifiable factor that could impact surgical outcome in FLE. Early diagnosis, presence of an MRI lesion not involving eloquent cortex, and ictal EEG without recruited rhythm independently predicted favorable outcome in this series. (C) 2011 Elsevier B.V. All rights reserved.

Organization Performance Evaluation Using System Thinking: A Study in Brazilian Chemical Organizations Models

System thinking allows companies to use subjective constructs indicators like recursiveness, cause-effect relationships and autonomy to performance evaluation. Thus, the question that motivates this paper is: Are Brazilian companies searching new performance measurement and evaluation models based on system thinking? The study investigates models looking for system thinking roots in their framework. It was both exploratory and descriptive based on a multiple four case studies strategy in chemical sector. The findings showed organizational models have some characteristics that can be related to system thinking as system control and communication. Complexity and autonomy are deficiently formalized by the companies. All data suggest, inside its context, that system thinking seems to be adequate to organizational performance evaluation but remains distant from the management proceedings.

Tracking the impact of translational research in psychiatry: state of the art and perspectives

Personalized treatments have become a primary goal in translational psychiatric research. They include the identification of neural circuits associated with psychiatric disorders and definition of treatment according to individual characteristics. Many new tools and technologies have been developed but further efforts are required to provide clues on how these scientific advances in psychiatry may be translated into more effective therapeutic approaches. Obstacles to the progress of translational psychiatry also involve numerous scientific, financial, ethical, logistics and regulatory aspects. Also, the goal of DSM-5 to expand “signs and symptoms” classification to incorporate biological measures may help the development of new multifactorial and dimensional models able to better understand the pathophysiology of psychiatric disorders and develop improved treatments. Finally, a better understanding on the significant response variability, cognitive functioning, role of comorbidities and treatment-resistant cases are critical for the development of prevention and intervention strategies that are more effective.

Fidelity and game-based technology in management education

This study explores educational technology and management education by analyzing fidelity in game-based management education interventions. A sample of 31 MBA students was selected to help answer the research question: To what extent do MBA students tend to recognize specific game-based academic experiences, in terms of fidelity, as relevant to their managerial performance? Two distinct game-based interventions (BG1 and BG2) with key differences in fidelity levels were explored: BG1 presented higher physical and functional fidelity levels and lower psychological fidelity levels. Hypotheses were tested with data from the participants, collected shortly after their experiences, related to the overall perceived quality of game-based interventions. The findings reveal a higher overall perception of quality towards BG1: (a) better for testing strategies, (b) offering better business and market models, (c) based on a pace that better stimulates learning, and (d) presenting a fidelity level that better supports real world performance. This study fosters the conclusion that MBA students tend to recognize, to a large extent, that specific game-based academic experiences are relevant and meaningful to their managerial development, mostly with heightened fidelity levels of adopted artifacts. Agents must be ready and motivated to explore the new, to try and err, and to learn collaboratively in order to perform.

Development of a supplier and purchase order management product/service under the 4PL logistics concept: a case study

Supply chain starts with a demand arisen and ends with material transport and delivery at its final destination. With this in mind, most of manufacturing, processors or distribution companies of consumer goods, spare parts and components for production, processing and finished goods, within national or international markets, may not have information and control over its supply chain performance. This article presents concept and logistics models evolution, purchase order and international supplier management, control tower and its logistics information systems. This also presents a real process implementation for a global high tech manufacturer company.

Phage display identification of CD100 in human atherosclerotic plaque macrophages and foam cells

Atherosclerosis is a complex disease in which vessels develop plaques comprising dysfunctional endothelium, monocyte derived lipid laden foam cells and activated lymphocytes. Considering that humans and animal models of the disease develop quite distinct plaques, we used human plaques to search for proteins that could be used as markers of human atheromas. Phage display peptide libraries were probed to fresh human carotid plaques, and a bound phage homologous to plexin B1, a high affinity receptor for CD100, was identified. CD100 is a member of the semaphorin family expressed by most hematopoietic cells and particularly by activated T cells. CD100 expression was analyzed in human plaques and normal samples. CD100 mRNA and protein were analyzed in cultured monocytes, macrophages and foam cells. The effects of CD100 in oxLDL-induced foam cell formation and in CD36 mRNA abundance were evaluated. Human atherosclerotic plaques showed strong labeling of CD100/SEMA4D. CD100 expression was further demonstrated in peripheral blood monocytes and in in vitro differentiated macrophages and foam cells, with diminished CD100 transcript along the differentiation of these cells. Incubation of macrophages with CD100 led to a reduction in oxLDL-induced foam cell formation probably through a decrease of CD36 expression, suggesting for the first time an atheroprotective role for CD100 in the human disease. Given its differential expression in the numerous foam cells and macrophages of the plaques and its capacity to decrease oxLDL engulfment by macrophages we propose that CD100 may have a role in atherosclerotic plaque development, and may possibly be employed in targeted treatments of these atheromas.

Extended spherical collapse and the accelerating universe

The influence of the shear stress and angular momentum on the nonlinear spherical collapse model is discussed in the framework of the Einstein–de Sitter and ΛCDM models. By assuming that the vacuum component is not clustering within the homogeneous nonspherical overdensities, we show how the local rotation and shear affect the linear density threshold for collapse of the nonrelativistic component (δc) and its virial overdensity (ΔV ). It is also found that the net effect of shear and rotation in galactic scale is responsible for higher values of the linear overdensity parameter as compared with the standard spherical collapse model (no shear and rotation)

Inhibitors of Trypanosoma brucei trypanothione reductase: comparative molecular field analysis modeling and structural basis for selective inhibition

Background: Sleeping sickness is a major cause of death in Africa. Since no secure treatment is available, the development of novel therapeutic agents is urgent. In this context, the enzyme trypanothione reductase (TR) is a prominent molecular target that has been investigated in drug design for sleeping sickness. Results: In this study, comparative molecular field analysis models were generated for a series of Trypanosoma brucei TR inhibitors. Statistically significant results were obtained and the models were applied to predict the activity of external test sets, with good correlation between predicted and experimental results. We have also investigated the structural requirements for the selective inhibition of the parasite's enzyme over the human glutathione reductase. Conclusion: The quantitative structure-activity relationship models provided valuable information regarding the essential molecular requirements for the inhibitory activity upon the target protein, providing important insights into the design of more potent and selective TR inhibitors.

Pharmacokinetic properties and in silico ADME modeling in drug discovery

The discovery and development of a new drug are time-consuming, difficult and expensive. This complex process has evolved from classical methods into an integration of modern technologies and innovative strategies addressed to the design of new chemical entities to treat a variety of diseases. The development of new drug candidates is often limited by initial compounds lacking reasonable chemical and biological properties for further lead optimization. Huge libraries of compounds are frequently selected for biological screening using a variety of techniques and standard models to assess potency, affinity and selectivity. In this context, it is very important to study the pharmacokinetic profile of the compounds under investigation. Recent advances have been made in the collection of data and the development of models to assess and predict pharmacokinetic properties (ADME - absorption, distribution, metabolism and excretion) of bioactive compounds in the early stages of drug discovery projects. This paper provides a brief perspective on the evolution of in silico ADME tools, addressing challenges, limitations, and opportunities in medicinal chemistry.